Database Reference
In-Depth Information
11. Freund, Y. and Mansour, Y. (1997). Learning under persistent drift.
Proceed-
ings of EuroColt
, pp. 109-118.
12. Gerevini, A., Perini, A., and Ricci, F. (1996). Incremental Algorithms for
Managing Temporal Constraints.
IEEE International Conference on Tools
with Artificial Intelligence (ICTAI'96
).
13. Harries, M. and Horn, K. (1996). Learning stable concepts in domains with
hidden changes in context.
Proceedings of the ICML-96 Workshop on Learn-
ing in Context-Sensitive Domains
, Bari, Italy, July 3, pp. 21-31.
14. Helmbold, D.P. and Long, P.M. (1994). Traching Drifting Concepts By Min-
imizing Disagreements.
Machine Learning
,
14
(1), 27-46.
15. Hsu, C.-N. and Knoblock, C.A. (1998). Discovering Robust Knowledge from
Databases that Change.
Journal of Data Mining and Knowledge Discovery
,
2
(1), 1-28.
16. Hines, W.H. and Montgomery, D.C. (1990).
Probability and Statistics in Engi-
neering and Management Science
. Third Edition, Wiley.
17. Jones, R.H., Crowell, D.H., and Kapuniai, L.E. (1970). Change detection
model for serially correlated multivariate data.
Biometrica
,
26
, 269-280.
18. Hulten, G., Spencer, L., and Domingos, P. (2001). Mining Time-Changing
Data Streams.
Proceedings of the Seventh ACM SIGKDD International Con-
ference on Knowledge Discovery and Data Mining (KDD-2001
).
19. Kelly, M.G., Hand, D.J., and Adams, N.M. (1999). The Impact of Chang-
ing Populations on Classifier Performance.
Proceedings of the Fifth ACM
SIGKDD International Conference on Knowledge Discovery and Data
Mining (KDD-99).
20. Kohavi, R. (1995). The Power of Decision Tables.
Proceedings of European
Conference on Machine Learning (ECML).
21. Lane, T. and Brodley, C.E. (1998). Approaches to Online and Concept Drift
for User Identification in Computer Security.
Proceedings of the Fourth Inter-
national Conference on Knowledge Discovery and Data Mining
, New York,
NY, pp. 259-263.
22. Last, M., Maimon, O., and Minkov, E. (2002). Improving Stability of Deci-
sion Trees.
International Journal of Pattern Recognition and Artificial Intel-
ligence
,
16
(2), 145-159.
23. Last, M. (2002). Online Classification of Non-stationary Data Streams.
Intelligent Data Analysis
,
6
(2), 129-147.
24. Liu, H. and Setiono, R. (1998). Incremental Feature Selection.
Journal of
Applied Intelligence
,
9
(3), 217-230.
25. Maimon, O. and Last, M. (2000).
Knowledge Discovery and Data Mining,
the Info-Fuzzy Network (IFN) Methodology
, Kluwer.
26. Martinez, T. (1990). Consistency and Generalization in Incrementally
Trained Connectionist Networks.
Proceeding of the International Symposium
on Circuits and Systems
, pp. 706-709.
27. Mangasarian, O.L. and Solodov, M.V. (1994). Backpropagation Convergence
via Deterministic Nonmonotone Perturbed Mininization.
Advances in Neural
Information Processing Systems
,
6
, 383-390.
